AIMC Topic: Algorithms

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Prediction analysis and quality assessment of microwell array images.

Electrophoresis
Microwell arrays are widely used for the analysis of fluorescent-labelled biomaterials. For rapid detection and automated analysis of microwell arrays, the computational image analysis is required. Support Vector Machines (SVM) can be used for this t...

Permutation Entropy and Signal Energy Increase the Accuracy of Neuropathic Change Detection in Needle EMG.

Computational intelligence and neuroscience
Needle electromyography can be used to detect the number of changes and morphological changes in motor unit potentials of patients with axonal neuropathy. General mathematical methods of pattern recognition and signal analysis were applied to recogn...

A Biologically Inspired Approach to Frequency Domain Feature Extraction for EEG Classification.

Computational and mathematical methods in medicine
Classification of electroencephalogram (EEG) signal is important in mental decoding for brain-computer interfaces (BCI). We introduced a feature extraction approach based on frequency domain analysis to improve the classification performance on diffe...

A Multiple Kernel Learning Model Based on -Norm.

Computational intelligence and neuroscience
By utilizing kernel functions, support vector machines (SVMs) successfully solve the linearly inseparable problems. Subsequently, its applicable areas have been greatly extended. Using multiple kernels (MKs) to improve the SVM classification accuracy...

Leveraging variable sensor spatial acuity with a homogeneous, multi-scale place recognition framework.

Biological cybernetics
Most robot navigation systems perform place recognition using a single-sensor modality and one, or at most two heterogeneous map scales. In contrast, mammals perform navigation by combining sensing from a wide variety of modalities including vision, ...

Sliding to predict: vision-based beating heart motion estimation by modeling temporal interactions.

International journal of computer assisted radiology and surgery
PURPOSE: Technical advancements have been part of modern medical solutions as they promote better surgical alternatives that serve to the benefit of patients. Particularly with cardiovascular surgeries, robotic surgical systems enable surgeons to per...

A Two-Stream Deep Fusion Framework for High-Resolution Aerial Scene Classification.

Computational intelligence and neuroscience
One of the challenging problems in understanding high-resolution remote sensing images is aerial scene classification. A well-designed feature representation method and classifier can improve classification accuracy. In this paper, we construct a new...

Semi-Supervised Discriminative Classification Robust to Sample-Outliers and Feature-Noises.

IEEE transactions on pattern analysis and machine intelligence
Discriminative methods commonly produce models with relatively good generalization abilities. However, this advantage is challenged in real-world applications (e.g., medical image analysis problems), in which there often exist outlier data points (sa...

Left Atrial Appendage Segmentation Using Fully Convolutional Neural Networks and Modified Three-Dimensional Conditional Random Fields.

IEEE journal of biomedical and health informatics
Thrombosis has become a global disease threatening human health. The left atrial appendage (LAA) is a major source of thrombosis in patients with atrial fibrillation (AF). Positive correlation exists between LAA volume and AF risk. LAA morphology has...